Bacha Sawssen, Taouali Okba, Liouane Noureeddine, "KELM-KPCA Method for COVID-19-induced Pneumonia Detection," WSEAS Transactions on Information Science and Applications, vol. 17, pp. 166-171, 2020, DOI:10.37394/23209.2020.17.20
Bacha Sawssen, Taouali Okba, Liouane Noureeddine. KELM-KPCA Method for COVID-19-induced Pneumonia Detection.
WSEAS Transactions on Information Science and Applications. 2020;17:166-171. 10.37394/23209.2020.17.20
WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 17, 2020
KELM-KPCA Method for COVID-19-induced Pneumonia Detection
Authors: , ,
Abstract: The new corona virus 2019 (COVID-19) has become the most pressing issue facing mankind. Like a wildfire burning through the world, the COVID-19 disease has changed the global landscape in only one year. In this mini-review, a novel image classifier based on Kernel Extreme Learning Machine (KELM) and Kernel Principal Component Analysis (KPCA) is presented. The proposed algorithm called KELM-KPCA, aims to detect COVID-19 disease in chest radiographs, using a constrained dataset.
Pages: 166-171 WSEAS Transactions on Information Science and Applications, ISSN / E-ISSN: 1790-0832 / 2224-3402, Volume 17, 2020, Art. #20 DOI: 10.37394/23209.2020.17.20
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